19/05/2021

The ‘Networking Archives’ Team

  • Worked is based on a larger project, thanks to (clockwise from left): Howard Hotson (Principal Investigator), Miranda Lewis, Matthew Wilcoxson, Arno Bosse, Philip Beeley, Ruth Ahnert (Co-Investigator), Sebastian Ahnert (Co-Investigator), Esther van Raamsdonk.

The Archival and Network Turns

  • The ‘archival turn’:

    • A phrase used by historians to describe the practice in recent years to focus critical attention on archives themselves
    • Archives are ‘texts’, contain layers of interpretation, at each step (collection, cataloguing, digitisation and so forth)
    • Challenges notion of archives as repositories of historical material and archivists as neutral custodians (Ketalaar 2001)
  • Ahnert et. al The Network Turn (2020) argues that we live in a networked world; this conference is evidence that this is true of historical scholarship.

  • What do we get at the intersection of the two?

Networks and Archives

  • Historical Network Research: letter archives (correspondence data) used to uncover communication practices or make claims about social relations.
  • However often the networks reveal as much or more about archival biases and practices as they do these things
  • I suggest we can use networks to talk about archives in their own right
  • What can network analysis tell us about the ‘text’ of archival processes?

Outline of the paper

  • Introduction to the ‘Networking Archives’ project and the archives used

  • Show some of the ways network analysis can be used to understand the shape and process of archives

    • Start with ways of looking for the overall shape
    • Move to more specific: what individual metrics tell us about archives
  • Finish with a more specific example of networks helping to find ‘new’ information in archives

The Archives Used

  • EMLO:
  • A union of c.100 catalogues brought together to study the republic of letters (1500-1800 but focus in 17th century)
  • Based on variety of sources, mostly printed editions but some from manuscript
  • In general catalogues are ‘ego networks:’ built around a static individual at the centre of a network.
  • SPO:
  • Digitised Calendars of scans of the State Papers from Britain and Ireland, Tudor and Stuart Periods (1509 - 1714)
  • Individual secretaries often viewed their official documents as ‘private’ and kept them as their possessions on leaving office:e.g. Conway Papers were only returned to the office in the 19th century

The Archives Used

  • When merged they make a large network of approximately 70,000 nodes and 120,000 edges, over 300 years.
  • The result is a ‘hairbrush’ force-directed diagram:
    • Tudor and Stuart connected to each other by a short edge: the ‘handle’ with early 16th century on one end and late 17th on the other.
    • EMLO and Stuart more focused on the 17th century and share more connections.

Using NA to understand the overall shape of the archives

  • Most basic analysis of these archives is to plot the degree distribution
  • Strikingly similar in all cases, despite very different origins of EMLO and SPO.
  • Implications for how we think about the archives: in all cases centred around a few ‘elite’ hubs:
  • Secretaries of State for SPO, and the figures at the centre of catalogues for EMLO

Catalogue Analysis

  • Created a network where each catalogue is a node, with an edge between them weighted on how many individuals shared by both
  • Result is a densely connected network which can show how each catalogue relates to each other
  • Three ‘core’ catalogues, State Papers Stuart, State Papers Tudor, Bodleian card catalogue
  • Visualisation shows some surprising connections, such as the strong overlap between Robert Boyle, Constantijn Huygens and the English State Papers.
  • Others on the ‘outside’: Johan de Witt, Athanasius Kircher, despite large collections are ‘separate’ to the ‘core’ of EMLO and State Papers. Different networks.

Catalogue Analysis

Catalogue Analysis using in and out-degree

High in-degree:

In-Degree Out-degree Catalogue
7243 6 Witt, Johan de
4813 3956 Huygens, Constantijn
3506 2356 Vossius, Gerardus Joannes
3407 410 Hartlib, Samuel
3347 2476 Oldenburg, Henry
3268 749 Lhwyd, Edward
3243 4916 Groot, Hugo de
2963 672 Andreae, Johann Valentin
2251 571 Kircher, Athanasius
1795 853 Vossius, Isaac

High out-degree:

In-degree Out-Degree Catalogue
3243 4916 Groot, Hugo de
4813 3956 Huygens, Constantijn
16 2483 Graffigny, Françoise de
3347 2476 Oldenburg, Henry
3506 2356 Vossius, Gerardus Joannes
312 2020 Peiresc, Nicolas-Claude Fabri de
1502 1519 Huygens, Christiaan
930 1452 Wallis, John
201 1170 Plantin, Christophe
769 953 Scaliger, Joseph Justus

Catalogue Analysis using in and out-degree

  • Simple metrics such as in and out-degree allow us to quickly understand the shape of various archives:

    • High in-degree, low out degree: Figures such as de Witt, a personal archive of collected letters: a ‘true’ archive as we might imagine it.
    • High out-degree, low in-degree: for example Françoise de Graffigny (1695–1758), archive of her collected and reassembled correspondence
    • Balance of both: tend to be reassembled collections, often based on printed editions or proejcts such as Constantijn Huygens (1596-1687) and Henry Oldenburg (1619-1677)

Archives and ‘closeness centrality’

  • Nodes with a high closeness score have a short distance to all other nodes (the inverse of the average distance to all other nodes)
  • In a series of connected archives, can tell which are more ‘embedded’ at the centre, and which at the periphery
  • Closeness is very related to degree: to find outliers, each archive in EMLO was ranked for closeness centrality and plotted against degree rank

Archives and ‘closeness centrality’

Archives and ‘closeness centrality’

  • The results help to describe the catalogues even with very minimal knowledge of their content

    • The ‘centre’ of EMLO is a group of mostly Dutch scholars
    • The archive of Athanasius Kircher is an anomaly: despite high degree, he is ranked lower than expected for closeness.
    • This tallies with our own knowledge: Kircher had a separate (though sometimes connected) network with the Republic of Letters. His inclusion in EMLO is an anomaly, separate to the core of its agenda.
    • On the other hand we have John Aubrey, whose closeness is surprisingly high for his degree: Aubrey was famously well-connected, member of the Royal Society, moved in both Royalist and Republican circles.
    • As new catalogues are added, can help to understand where they are situated, in a glance

Looking for intercepted letters in disconnected components

  • The State Papers have a complicated history:

    • Mostly the personal papers of individual secretaries of state
    • But also includes seized documents, intercepted papers, whole bunches of documents captured from ships (see also the Prize Papers)
    • Some simple tools from network analysis can also help to discover some of these

Disconnected Components

  • Most of the State Papers consists of one ‘giant component’: every node can reach every other
  • However there are some completely ‘disconnected’ components
  • These make interesting starting-points for investigations
  • Many are intercepted or seized documents

Disconnected Components

Disconnected Components

Disconnected Components

  • Seized letters from Dr. Richard Smith, Roman Catholic Bishop
  • Warrant was issued for Smith’s arrest in 1628
  • He fled England for France, presumably when his letters were found and added to the State Papers
  • A secretary or clerk has added ‘Papist’ when filing, indicating these were suspect communications




Disconnected Components


Disconnected Components

Conclusions

  • NA based on historical archives often tells us more about collection than it does about communication practices (e.g a particular centrality might not reflect a node’s position but rather the way that archive has been collected and digitised)
  • This can be a positive thing if focus is shifted to archives themselves
  • If archives are texts, it follows that we can apply ‘distant reading’ to them
  • Network analysis can help us understand what Eric Ketalaar calls the ‘tacit narratives of power and knowledge’ found in archives
  • If archives are ‘texts’, then it follows that we can apply ‘distant reading’ to them
  • Help to understand their formation as active objects rather than passive silos of information
  • As more archives are merged this can help to understand differences between them